Can LSTM Nets be speed up by GPU?
From nvidia www (https://developer.nvidia.com/discover/lstm):

Accelerating Long Short-Term Memory using GPUs

The parallel processing capabilities of GPUs can accelerate the LSTM training and inference processes. GPUs are the de-facto standard for LSTM usage and deliver a 6x speedup during training and 140x higher throughput during inference when compared to CPU implementations. cuDNN is a GPU-accelerated deep neural network library that supports training of LSTM recurrent neural networks for sequence learning. TensorRT is a deep learning model optimizer and runtime that supports inference of LSTM recurrent neural networks on GPUs. Both cuDNN and TensorRT are part of the NVIDIA Deep Learning SDK.